Chapter 1 introduces you to missing data, explaining what missing values are, their behavior in R, how to detect them, and how to count them. We then introduce missing data summaries and how to summarise missingness across cases, variables, and how to explore across groups within the data. Finally, we discuss missing data visualizations, how to produce overview visualizations for the entire dataset and over variables, cases, and other summaries, and how to explore these across groups.
Exercise 1: Introduction to missing dataExercise 2: Using and finding missing valuesExercise 3: How many missing values are there?Exercise 4: Working with missing valuesExercise 5: Why care about missing values?Exercise 6: Summarizing missingnessExercise 7: Tabulating MissingnessExercise 8: Other summaries of missingnessExercise 9: How do we visualize missing values?Exercise 10: Your first missing data visualizationsExercise 11: Visualizing missing cases and variablesExercise 12: Visualizing missingness patterns